Technical Lead - Artificial Intelligence

Job Role

As an AI Expert with minimum 10 years of experience, you will play a critical role in our organization by serving as a technical expert and solving technical blockers faced by our development teams. Your primary responsibility will be to provide guidance and expertise in the development and implementation of AI solutions. You will work closely with cross-functional teams to ensure successful integration of AI technologies into our products and services. Additionally, your role will involve actively participating in Agile methodologies, with a focus on Scaled Agile and PI planning.

Key Responsibilities

• Development Governance
• Guide internal and external developers and helps to remove technical dependencies and impediments during the product development.
• Support Product Owner from technical perspective
• Support in technical planning of the product
• Define enablers for the product backlog
• Consult AI Architect for questions regarding technical requirements
• Contribute to the self-organizing spirit of agile delivery teams and work in a full agile process (taking part in necessary ceremonies,etc.)
• Provide technical expertise and guidance to development teams in the implementation of AI solutions.
• Analyze and understand technical requirements and propose AI-based solutions to address complex problems.
• Collaborate with cross-functional teams to design and develop AI models and algorithms that meet business objectives.
• Investigate and resolve technical blockers and challenges faced by development teams during the AI implementation process.
• Stay up to date with the latest advancements and trends in AI technologies and bring innovative ideas to the organization.
• Actively participate in Agile methodologies, including Scaled Agile Framework (SAFe), and contribute to PI planning, backlog grooming, and sprint reviews.
• Conduct code reviews, provide constructive feedback, and mentor junior team members in AI best practices and techniques.
• Collaborate with stakeholders to identify opportunities for applying AI technologies and drive their adoption across the organization.
  
  

Qualifications, Experience & Skills

Mandatory skills, competencies & certifications:

(Education, Experience, Software / Tools, Etc.)

• Bachelor's or master’s degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience working in the field of AI, with a focus on solving technical challenges and implementing AI solutions.
• Strong knowledge and understanding of AI technologies, including machine learning, deep learning, natural language processing, and computer vision.
• Deep understanding of AI design patterns as well as their immediate
• implementation, Deep technical understanding of data processing for consumption/delivery by AI micro services,
• Established knowledge of modern software development and micro service frameworks
• Deep understanding of relevant technology landscape for AI&BI products
• Proficiency in programming languages such as Python, R, or Java, and experience with popular AI frameworks (e.g., TensorFlow, PyTorch).
• In-depth understanding of Agile methodologies, especially Scaled
• Agile Framework (SAFe), and experience with PI planning and related activities.
• Excellent problem-solving and analytical skills, with the ability to think creatively and propose innovative AI-based solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and stakeholders.
• Proven track record of successfully delivering AI projects and overcoming technical challenges in complex environments.
  
  

General

Preferred skills, competencies & certifications:

• Very high proficiency in Python
• Very high proficiency in the most common python libraries for data science and machine learning: Pandas, Numpy, Scikit-Learn, SciPy, Statsmodels, Keras, TensorFlow, PyTorch, Matplotlib.
• High proficiency in dependency management via Pip and Conda
• High proficiency in code versioning via Git
• Hgh proficiency with Jupyter notebooks
• Very good knowledge of MLFlow, both operational and deployment strategies/architectures on cloud and on premise
• Very good knowledge of Spark (pyspark), Kafka, Hadoop, and data formats for Big Data
• Good knowledge of flask for the development of microservices
• Good knowledge of containerization via Docker
• Good knowledge of Openshift
• Optional: data visualization tools (Power BI, Tableau)
  
  

Cloud

• Azure Machine Learning
• Azure Language Service
• Azure OpenAI Service
• Azure Data Lake
• Azure Kubernetes Service
• Databricks